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Regional Structure Modelling and Source Inversion for the 1992 Roermond Earthquake

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Regional Structure Modelling and Source Inversion for the 1992 Roermond Earthquake IC/97/14 United Nations Educational Scientific and Cultural Organization and International Atomic Energy Agency INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS REGIONAL STRUCTURE MODELLING AND SOURCE INVERSION FOR THE 1992 ROERMOND EARTHQUAKE H. Dufumier1 Dipartimento di Scienze della Terra, via Weiss 1, Trieste, Italy, A. Michelini2 Dipartimento di Scienze della Terra, via Weiss 1, Trieste, Italy, Z. Du International Centre for Theoretical Physics, SAND Group, Trieste, Italy and Dipartimento di Scienze della Terra, via Weiss 1, Trieste, Italy, I. Bondar International Centre for Theoretical Physics. SAND Group, Trieste, Italy and Seismological Observatory, Hungarian Academy of Sciences, Meredek u. 18, 1112 Budapest, Hungary, J, Sileny Geophysical Institute, Academy of Sciences of the Czech Republic, Bocni 11/1401, 141 31-Praha 4, Czech Republic, W. Mao Department of Earth Sciences, University of Leeds. Leeds LS2 9JT. United Kingdom, S. Kravanja Dipartimento di Scienze della Terra, via Weiss 1, Trieste, Italy and G.F. Panza International Centre for Theoretical Physics, SAND Group, Trieste, Italy and Dipartimento di Scienze della Terra, via Weiss 1. Trieste, Italy. MIRAMARE - TRIESTE February 1997 1Present address: Institut de Physique du Globe, 5 rue Descartes, 67084 Strasbourg Cedex, France. 2Prcsent address: Osservatorio Geofisico Sperimentale, P.O. Box 2011, Opicina, Italy. Abstract: The Mw = 5.4 Roermond earthquake of April 13, 1992, is used as a "test" earthquake for the development of source inversion methods at a regional scale in Europe. We combine structural modelling of the European continent (Du et al., 1997) with two source inversion methods derived from Sileny et al. (1992), and Mao et al. (1994). We show that following this strategy, it is possible to fully analyze the inverse problem of the hypocentral relocation, source mechanism and rupture history. We define and discuss our methodology on the basis of the inverse problem and of the associated tools. The results of our application to the Roermond earthquake are discussed at the light of other previously published solutions. Such an approach appears to offer a promising tool for the global description of seismic sources in regions well studied from the structural point of view, through waveform inversion of a few regional records. Key Words: Roermond, Source Inversion, Regional structure. Introduction The April 13, 1992, Mw = 5.4 Roermond earthquake, in the Roer Valley Graben (The Netherlands), belongs to the largest earthquakes which occurred in North-Western Europe in this century. It has already been extensively studied with different approaches. We refer to Geluk et al (1994), van den Berg (1994) and Trifonov et al. (1994) for the geological aspects, to Camelbeeck and van Eck (1994) and Camelbeeck et al. (1994) for the seismological studies of the main event and of its aftershocks, and more generally to the special issue published about this earthquake by van Eck and Davenport (1994) for an extensive overview of seismic hazard, tectonic, seismological, engineering and hydrogeological aspects. Concerning the source inversions for this earthquake, we note the CMT solution at a global scale (Dziewonski et al., 1993), and the regional scale inversion by Braumiller et al. (1994). Loohuis and van Eck (1996) also presented a joint inversion for the regional source mechanisms and stress tensor. This earthquake is used as a 'test' earthquake to improve new developments in regional structure modelling and source inversion at the European scale. In fact developments in these two scismological fields should not be disconnected, since source retrieval highly depends on path effects at the regional scale, as at the global scale (Dufumier and Trampert, 1997). We combine structural modelling, derived from the regional I-data set for the European continent (Du et al., 1997) with two source inversion methods derived from local-scale methods (Sileny and Panza, 1991; Mao el al., 1994). In particular, we consider waveform inversions in time domain of the vertical component of motion. /. Structural modelling Regional studies require accurate modelling of the geological structures in the region of interest. We show in figure 1 the six regional paths for which broadband data were easily available on line in the first years following the event, and used in this study. Available data from other stations too close to these ones were not considered, since they would not bring independant information (cf Dufumier and Cara, 1995) and lead to undesirable data redundancy effects (Michelini, 1997). We use the three-dimensional I-data set model of Europe (Du el al., 1997) to obtain cross- sections of the crustal and lithospheric structures along these paths. The I-data set of Europe is a 3 - D structural model of the tcctosphcrc. This model has been assembled from the published literature and it includes all the principal geological and tectonic features that have been recognized on the regional scale. The I-data set is made out of approximately 6000 1-D structures and linear interpolation is used throughout to find P-wave and S-wave velocities, density and attenuation within the structure. As illustration, we present in figure 2 our most heterogeneous cross-section, corresponding to the great circle path Roermond - ESK. Overall, the I-data set has been found to provide reliable dispersion measurements on the whole Euro-Mediterranean domain for periods greater than 15 seconds (Du et a!., 1997). However, to obtain detailed information on the source mechanism, it is necessary to model the wavcficld, i.e. to determine the Green's functions, at shorter periods. Because existing methods for forward modelling in 3-D or across 2-D cross-section (e.g. finite differences, ray methods or boundary integrals) arc either computationally expensive, or require decomposition of the wavefield, we follow the simpler approach of averaging the 3-D I-data set model into 1 -D structures along each source-receiver path, and forward modelling is performed using a modal summation method (e.g. Panza, 1985). If the 2-D cross-section of the I-data set model would have displayed strong discontinuities, it would have been necessary to use 2-D modal summation methods, including transmission and coupling at the interfaces (Vaccari et ai., 1989), but this is not the case for the region we examine here. Averaging, however, may remove a significant part of the original 3-D information and, therefore, it should be performed with caution, to preserve the information pertinent for source inversion. We considered here two types of averaging: - the first one, called "layer-averaging", preserves the layer discontinuities through interpolation within crustal and mantle layers separately, averaging the depths of the main interfaces. - the second one, called "depth-averaging", averages the velocities at each depth along the source-receiver path, and results into a more continuous model. The 1 -D models obtained using the two types of averaging arc presented in figure 3 for the six paths of figure 1. We also show the model for the source region as determined from the I-data set. This model is consistent with those published in the literature (e.g. Trifonov et ai., 1994). The effects of averaging on the source inversion will be studied in the next part; but it can already be noted that it affects significantly the dispersion of the first modes (figure 4a), and, therefore, the synthetic waveforms used in the inversion (figure 4c). To ensure that both data and synthetics have a similar time-frequency content, we apply to both sets a variable-period velocity filter (Levshin et ai., 1972; Cara, 1973). The filtering limits are fixed from the double observation of the data spectrogram (or multiple time-frequency analysis, sec Kocaoglu and Long, 1993, for a review of the techniques) and of the dispersion curves associated to the structure. An example is shown on figure 4, for the path Rocmnond-WET. In figure 4a we present the synthetic dispersion curves, according to the two averaging methods; while in figure 4b we show the spectrogram of the observed data (following Levshin el ai., 1992), with the selected filtering window. Figure 4c shows the effect of the variable filter on the original data and on corresponding synthetic seismograms, considering the two types of averaged structures. It can be seen that the use of an appropriate filtering window can help to adjust the time-frequency content of the synthetic seismograms to the data one without removing information from the original waveform. We also use similar filtering windows for the other paths. In addition, a common low pass filtering is applied to all the seismograms, defining the lowest period to be used in the inversion. This period can be adjusted, depending on the preference given to the resolution of the source model or to the quality of data fitting. We used cutting periods of 1 to 10 seconds, the most significative results shown here corresponding to cutting periods around 3 to 5 seconds. Thirty modes arc used to fit the time-frequency content of the data, so that we achieve the complete theoretical modelling of the seismograms from the S-wave to the end of the direct Raylcigh wave. The major part of the signal is kept in the inversion windows, corresponding to the zone of good signal to noise ratio that can be satisfactorily fitted using the summation of the most energetic modes. Anyhow, the data of the station HAM were not kept in short-period inversions, because the local influence of the Northern Germany sedimentary basin could not be correctly taken into account from short-period derivations of the I-data set model. The methodology of data processing developed here will now allow us to perform waveform inversions of complete seismograms at a regional scale, where information on source and structures usually strongly mix together. //. Extended Monte-Carlo search In our first source inversion method, we want to consider the possible trade-offs between source and structural parameters, without constraining the solution with a priori assumptions.
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